The Effects of Simulation Complexity and Hypothesis-Generation Strategy on Learning
The Effects of Simulation Complexity and Hypothesis-Generation Strategy on Learning
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模拟复杂性和假设生成策略对学习的影响
DOI：
10.1080/08886504.1994.10782117
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发表时间：
1994
期刊：
影响因子：
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通讯作者：
A. Stephen
中科院分区：
文献类型：
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作者：
Q. James;A. Stephen
摘要本研究考察了计算机模拟学习作为两个因素的作用：学习者的假设生成策略和模拟呈现形式。模拟演示格式是指模拟最初是以最复杂的形式演示，还是以日益复杂的部分演示。主要有三个发现。首先，假设生成策略(生成一个或多个初始假设)与复杂性之间存在交互作用。将模拟分成复杂性增加的部分并不会增加总体任务的成功率，但确实会提高生成几个假设的受试者在复杂性最低部分的表现。当复杂性较低时，受试者更有可能产生几个假设。其次，当模拟包含一个行为与直觉相反的变量时，生成几个假设是有帮助的。第三，当复杂性较低时，处于多假设条件下的受试者具有更高的认知能力。
AbstractThis study investigated learning with computer simulation as a function of two factors: learners’ hypothesis-generation strategy and simulation presentation format. Simulation presentation format refers to whether the simulation was presented in its most complex form initially or whether it was presented in sections of increasing complexity. There were three main findings. First, there was an interaction between hypothesis-generation strategy (generating one versus several initial hypotheses) and complexity. Breaking the simulation into sections of increasing complexity did not increase overall task success but did improve performance on the section of lowest complexity for subjects generating several hypotheses. When complexity was low, subjects were more likely to generate several hypotheses. Second, generating several hypotheses was helpful when the simulation contained a variable that behaved counterintuitively. Third, when complexity was low, subjects in the multiple-hypothesis condition atte...